Concurrency Control Techniques

About This Presentation

Title:

Concurrency Control Techniques

Description:

A transaction applies locks (read or write) on desired data items one at a time. ... Same schedule may not be allowed under each protocol. ... – PowerPoint PPT presentation

Number of Views:220

Avg rating:3.0/5.0

Slides: 42

Provided by: sdmine

Learn more at: https://sdmines.sdsmt.edu

Category:

more less

Transcript and Presenter's Notes

Title: Concurrency Control Techniques

1
Chapter 18

Concurrency Control Techniques

2
Database Concurrency Control

Purpose of Concurrency Control
To enforce Isolation (through mutual exclusion)
among conflicting transactions.
To preserve database consistency through
consistency preserving execution of transactions.
To resolve read-write and write-write conflicts.
Example
In concurrent execution environment if T1
conflicts with T2 over a data item A, then the
existing concurrency control decides if T1 or T2
should get the A and if the other transaction is
rolled-back or waits.

3
Two-Phase Locking Techniques

Two-Phase Locking Techniques
Locking is an operation which secures
(a) permission to Read
(b) permission to Write a data item for a
transaction.
Example
Lock (X). Data item X is locked in behalf of the
requesting transaction.
Unlocking is an operation which removes these
permissions from the data item.
Example
Unlock (X) Data item X is made available to all
other transactions.
Lock and Unlock are Atomic operations.

4
Two-Phase Locking Techniques (2)

Essential components
Two locks modes
(a) shared (read) (b) exclusive (write).
Shared mode shared lock (X)
More than one transaction can apply share lock on
X for reading its value but no write lock can be
applied on X by any other transaction.
Exclusive mode Write lock (X)
Only one write lock on X can exist at any time
and no shared lock can be applied by any other
transaction on X.
Conflict matrix

5
Two-Phase Locking Techniques (3)

Essential components
Lock Manager
Managing locks on data items.
Lock table
Lock manager uses it to store the identify of
transaction locking a data item, the data item,
lock mode and pointer to the next data item
locked. One simple way to implement a lock table
is through linked list.

6
Two-Phase Locking Techniques (4)

Essential components
Database requires that all transactions should be
well-formed. A transaction is well-formed if
It must lock the data item before it reads or
writes to it.
It must not lock an already locked data items and
it must not try to unlock a free data item.

7
Two-Phase Locking Techniques (5)

Essential components
The following code performs the lock operation
B if LOCK (X) 0 (item is unlocked)
then LOCK (X) ? 1 (lock the item)
else begin
wait (until lock (X) 0) and
the lock manager wakes up the transaction)
goto B
end

8
Two-Phase Locking Techniques (6)

Essential components
The following code performs the unlock operation
LOCK (X) ? 0 (unlock the item)
if any transactions are waiting then
wake up one of the waiting the transactions

9
Two-Phase Locking Techniques (7)

Essential components
The following code performs the read lock
operation
B if LOCK (X) unlocked then
begin LOCK (X) ? read-locked
no_of_reads (X) ? 1
end
else if LOCK (X) ? read-locked then
no_of_reads (X) ? no_of_reads (X) 1
else begin wait (until LOCK (X) unlocked
and
the lock manager wakes up the transaction)
go to B
end

10
Two-Phase Locking Techniques (8)

Essential components
The following code performs the write lock
operation
B if LOCK (X) unlocked then
LOCK (X) ? write-locked
else begin wait (until LOCK (X) unlocked
and
the lock manager wakes up the transaction)
go to B
end

11
Two-Phase Locking Techniques (9)

Essential components
The following code performs the unlock operation
if LOCK (X) write-locked then
begin LOCK (X) ? unlocked
wakes up one of the transactions, if any
end
else if LOCK (X) ? read-locked then
begin
no_of_reads (X) ? no_of_reads (X) -1
if no_of_reads (X) 0 then
begin
LOCK (X) unlocked
wake up one of the transactions, if any
end
end

12
Two-Phase Locking Techniques (10)

Essential components
Lock conversion
Lock upgrade existing read lock to write lock
if Ti has a read-lock (X) and Tj has no
read-lock (X) (i ? j) then
convert read-lock (X) to write-lock (X)
else
force Ti to wait until Tj unlocks X
Lock downgrade existing write lock to read lock
Ti has a write-lock (X) (no transaction can
have any lock on X)
convert write-lock (X) to read-lock (X)

13
Two-Phase Locking Techniques (11)

Two-Phase Locking Techniques The algorithm
Two Phases
(a) Locking (Growing)
(b) Unlocking (Shrinking).
Locking (Growing) Phase
A transaction applies locks (read or write) on
desired data items one at a time.
Unlocking (Shrinking) Phase
A transaction unlocks its locked data items one
at a time.
Requirement
For a transaction these two phases must be
mutually exclusively, that is, during locking
phase unlocking phase must not start and during
unlocking phase locking phase must not begin.

14
Two-Phase Locking Techniques (12)

Two-Phase Locking Techniques The algorithm
T1 T2 Result
read_lock (Y) read_lock (X) Initial
values X20 Y30
read_item (Y) read_item (X) Result of
serial execution
unlock (Y) unlock (X) T1 followed by T2
write_lock (X) Write_lock (Y) X50, Y80.
read_item (X) read_item (Y) Result of
serial execution
XXY YXY T2 followed by T1
write_item (X) write_item (Y) X70, Y50
unlock (X) unlock (Y)

15
Two-Phase Locking Techniques (13)

Two-Phase Locking Techniques The algorithm
T1 T2 Result
read_lock (Y) X50 Y50
read_item (Y) Nonserializable because
it.
unlock (Y) violated two-phase policy.
read_lock (X)
read_item (X)
unlock (X)
write_lock (Y)
read_item (Y)
YXY
write_item (Y)
unlock (Y)
write_lock (X)
read_item (X)
XXY
write_item (X)
unlock (X)

16
Two-Phase Locking Techniques (14)

Prevents Lost Update problem using 2PL
T2 first requests and receives an exclusive lock
on balx. T1 must wait until the lock is released
by T2.

17
Two-Phase Locking Techniques (15)

Schedule with T17 and T18 (below) follows the 2PL
protocol but they are in deadlock

18
Two-Phase Locking Techniques (16)

Two-Phase Locking Techniques The algorithm
Two-phase policy generates two locking algorithms
(a) Basic
(b) Conservative
Conservative
Prevents deadlock by locking all desired data
items before transaction begins execution.
Basic
Transaction locks data items incrementally. This
may cause deadlock which is dealt with.
Strict
A more stricter version of Basic algorithm where
unlocking is performed after a transaction
terminates (commits or aborts and rolled-back).
This is the most commonly used two-phase locking
algorithm.

19
Dealing with Deadlock and Starvation

Deadlock
T1 T2
read_lock (Y) T1 and T2 did follow two-phase
read_item (Y) policy but they are deadlock
read_lock (X)
read_item (Y)
write_lock (X)
(waits for X) write_lock (Y)
(waits for Y)
Deadlock (T1 and T2)

20
Dealing with Deadlock Starvation (2)

Deadlock prevention
A transaction locks all data items it refers to
before it begins execution.
This way of locking prevents deadlock since a
transaction never waits for a data item.
The conservative two-phase locking uses this
approach.

21
Dealing with Deadlock Starvation (3)

Deadlock detection and resolution
In this approach, deadlocks are allowed to
happen. The scheduler maintains a wait-for-graph
for detecting cycle. If a cycle exists, then one
transaction involved in the cycle is selected
(victim) and rolled-back.
A wait-for-graph is created using the lock table.
As soon as a transaction is blocked, it is added
to the graph. When a chain like Ti waits for Tj
waits for Tk waits for Ti or Tj occurs, then this
creates a cycle.
One of the transaction (called victim) must be
aborted to avoid the deadlock.

22
Dealing with Deadlock Starvation (4)

Deadlock avoidance
There are many variations of two-phase locking
algorithm.
Some avoid deadlock by not letting the cycle to
complete.
That is as soon as the algorithm discovers that
blocking a transaction is likely to create a
cycle, it rolls back the transaction.
Wound-Wait and Wait-Die algorithms use timestamps
to avoid deadlocks by rolling-back victim.

23
Deadlock Avoidance algorithms

Wait-Die - only an older transaction can wait for
younger one, otherwise transaction is aborted
(dies) and restarted with same timestamp.
Wound-Wait - only a younger transaction can wait
for an older one. If older transaction requests
lock held by younger one, younger one is aborted
(wounded).

24
Dealing with Deadlock Starvation (5)

Starvation
Starvation occurs when a particular transaction
consistently waits or restarted and never gets a
chance to proceed further.
In a deadlock resolution it is possible that the
same transaction may consistently be selected as
victim and rolled-back.
This limitation is inherent in all priority based
scheduling mechanisms.
In Wound-Wait scheme a younger transaction may
always be wounded (aborted) by a long running
older transaction which may create starvation.

25
Timestamp concurrency control

Timestamp
A monotonically increasing variable (integer)
indicating the age of an operation or a
transaction. A larger timestamp value indicates
a more recent event or operation.
Timestamp based algorithm uses timestamp to
serialize the execution of concurrent
transactions.
Timestamps are assigned to each transaction and
to data items
TS(T) The timestamp of transaction T
Read_TS(X) The read timestamp of data item X
Write_TS(X) the write timestamp of data item X

26
Timestamp concurrency control (2)

Basic Timestamp Ordering
1. Transaction T issues a write_item(X)
operation
a) If read_TS(X) gt TS(T) or if write_TS(X) gt
TS(T), then an younger transaction has already
read or written the data item so abort and
roll-back T and reject the operation.
b) If the condition in part (a) does not exist,
then execute write_item(X) of T and set
write_TS(X) to TS(T).
2. Transaction T issues a read_item(X)
operation
If write_TS(X) gt TS(T), then an younger
transaction has already written to the data item
so abort and roll-back T and reject the
operation.
If write_TS(X) ? TS(T), then execute read_item(X)
of T and set read_TS(X) to the larger of TS(T)
and the current read_TS(X).

27
Example
28
Timestamp concurrency control (3)

Strict Timestamp Ordering
A variation of basic TO It ensures that
schedules are both, strict and serializable
1. Transaction T issues a write_item(X)
operation
If TS(T) gt read_TS(X), then delay T until the
transaction T that wrote or read X has
terminated (committed or aborted).
2. Transaction T issues a read_item(X)
operation
If TS(T) gt write_TS(X), then delay T until the
transaction T that wrote or read X has
terminated (committed or aborted).

29
Timestamp concurrency control (4)

Thomass Write Rule
It does not enforce conflict serializability, but
it rejects fewer write operations
If read_TS(X) gt TS(T) then abort and roll-back T
and reject the operation.
If write_TS(X) gt TS(T), then just ignore the
write operation and continue execution. This is
because the most recent writes counts in case of
two consecutive writes.
If the conditions given in 1 and 2 above do not
occur, then execute write_item(X) of T and set
write_TS(X) to TS(T).

30
Timestamp concurrency control (5)

TO detects two conflicting operations that occur
in the incorrect order
The schedules produced by basic TO are guaranteed
to be conflict serializable, like the 2PL
Same schedule may not be allowed under each
protocol.
Neither protocol allows all possible serializable
schedules
But deadlock does not occur with TO
However, starvation may occur if a transaction is
continuously aborted and restarted

31
Multiversion concurrency control

This approach maintains a number of versions of a
data item and allocates the right version to a
read operation of a transaction. Thus unlike
other mechanisms a read operation in this
mechanism is never rejected.
Side effect
Significantly more storage (RAM and disk) is
required to maintain multiple versions. To check
unlimited growth of versions, a garbage
collection is run when some criteria is
satisfied.

32
Optimistic concurrency control

In this technique only at the time of commit
serializability is checked and transactions are
aborted in case of non-serializable schedules.
Three phases
Read phase
Validation phase
Write phase
1. Read phase
A transaction can read values of committed data
items. However, updates are applied only to
local copies (versions) of the data items (in
database cache).

33
Optimistic concurrency control (2)

2. Validation phase Serializability is checked
before transactions write their updates to the
database.
This phase for Ti checks that, for each
transaction Tj that is either committed or is in
its validation phase, one of the following
conditions holds
Tj completes its write phase before Ti starts its
read phase.
Ti starts its write phase after Tj completes its
write phase, and the read_set of Ti has no items
in common with the write_set of Tj
Both the read_set and write_set of Ti have no
items in common with the write_set of Tj, and Tj
completes its read phase.
When validating Ti, the first condition is
checked first for each transaction Tj, since (1)
is the simplest condition to check. If (1) is
false then (2) is checked and if (2) is false
then (3 ) is checked. If none of these
conditions holds, the validation fails and Ti is
aborted.

34
Optimistic concurrency control (3)

3. Write phase On a successful validation
transactions updates are applied to the
database otherwise, transactions are restarted.

35
Granularity of data items

A lockable unit of data defines its granularity.
Granularity can be coarse (entire database) or it
can be fine (a tuple or an attribute of a
relation).
Data item granularity significantly affects
concurrency control performance. Thus, the degree
of concurrency is low for coarse granularity and
high for fine granularity.
Example of data item granularity
A field of a database record (an attribute of a
tuple)
A database record (a tuple or a relation)
A disk block
An entire file
The entire database

36
Multiple granularity level

The following diagram illustrates a hierarchy of
granularity from coarse (database) to fine
(record).

37
Multiple granularity level (2)

To manage such hierarchy, in addition to read and
write, three additional locking modes, called
intention lock modes are defined
Intention-shared (IS) indicates that a shared
lock(s) will be requested on some descendent
nodes(s).
Intention-exclusive (IX) indicates that an
exclusive lock(s) will be requested on some
descendent node(s).
Shared-intention-exclusive (SIX) indicates that
the current node is locked in shared mode but an
exclusive lock(s) will be requested on some
descendent nodes(s).

38
Multiple granularity level (3)

These locks are applied using the following
compatibility matrix

Intention-shared (IS Intention-exclusive
(IX) Shared-intention-exclusive (SIX)
39
Multiple granularity level (4)

The set of rules which must be followed for
producing serializable schedule are
The lock compatibility must adhered to.
The root of the tree must be locked first, in any
mode..
A node N can be locked by a transaction T in S or
IX mode only if the parent node is already locked
by T in either IS or IX mode.
A node N can be locked by T in X, IX, or SIX mode
only if the parent of N is already locked by T in
either IX or SIX mode.
T can lock a node only if it has not unlocked any
node (to enforce 2PL policy).
T can unlock a node, N, only if none of the
children of N are currently locked by T.